Dehydration liquid treatment optimization method for safe recycling system

Abstract

The invention provides a dehydration liquid treatment optimization method for a safe recycling system, and relates to the technical field of data processing.The dehydration liquid treatment optimization method comprises the steps that sample collection is conducted on to-be-treated dehydration liquid, and an impurity analysis object is obtained; detecting and analyzing the impurity analysis object to obtain an impurity proportion parameter set; presetting a reuse association information set, and positioning an impurity extraction deviation set in the impurity proportion parameter set according to the reuse association information set; performing impurity removal correlation step analysis based on the impurity extraction deviation set, and performing process parameter configuration of the safety reuse system based on an analysis result; and the configured safe recycling system is used for impurity removal and recycling of the to-be-treated dehydrated liquid. The technical problem that in the prior art, setting of process step parameters in the dehydration liquid treatment process excessively depends on experience and intuition of operators, and consequently the dehydration liquid treatment efficiency is affected is solved. The technical effects of intelligentization and optimization of the dehydration liquid treatment process, improvement of the treatment efficiency and the water quality and guarantee of safe reuse of the dehydration liquid are achieved.

Description

Technical Field

[0001] The invention relates to the technical field of data processing, and in particular to a dewatering liquid processing optimization method for a safe reuse system. Background Art

[0002] Existing dehydration liquid treatment processes often rely too much on the operator's experience and intuition in parameter setting. For example, operators need to judge the concentration of pollutants based on the color, smell or simple chemical tests of the dehydration liquid, and adjust the pH value, the amount of flocculant or disinfectant added accordingly. This method that relies on personal experience lacks accuracy and consistency, because different operators may have different judgments and operating habits, resulting in fluctuations in treatment results.

[0003] Also, without accurate data to support this, operators may add unnecessary treatment steps, such as excessive agitation or repeated filtration, which increase treatment cost and time while having limited effect on improving water quality.

[0004] Due to inaccurate process parameter settings, the treatment system may not operate under optimal conditions, resulting in low treatment efficiency. The instability in the treatment process will also affect the water quality stability of the recycled water.

[0005] In summary, the prior art has the problem that the process parameter setting of the dehydration liquid treatment process is overly dependent on the operator's experience and intuition, resulting in unnecessary steps or omission of key steps in the dehydration liquid treatment process, thereby affecting the dehydration liquid treatment efficiency and the water quality stability of the recycled water. Summary of the invention

[0006] The present application provides a method for optimizing the treatment of dehydrated liquid for a safe reuse system, which is used to solve the technical problem in the prior art that the process step parameter setting of the dehydrated liquid treatment process is overly dependent on the operator's experience and intuition, resulting in unnecessary steps or omission of key steps in the dehydrated liquid treatment process, thereby affecting the dehydrated liquid treatment efficiency and the water quality stability of the obtained reused water.

[0007] In view of the above problems, the present application provides a method for optimizing the treatment of dehydrated liquid for a safe reuse system.

[0008] The present application provides a method for optimizing the treatment of dehydrated liquid for a safe reuse system, comprising: collecting samples of the dehydrated liquid to be treated to obtain an impurity analysis object; detecting and analyzing the impurity analysis object to obtain an impurity ratio parameter set; presetting a reuse association information set, and locating an impurity extraction deviation set in the impurity ratio parameter set according to the reuse association information set; performing an impurity removal association step analysis based on the impurity extraction deviation set, and configuring the process parameters of the safe reuse system based on the analysis results; and using the configured safe reuse system to remove impurities and reuse the dehydrated liquid to be treated.

[0009] In a possible implementation, the reuse-related information set includes a plurality of reuse-related indicators and a plurality of reuse-related requirements.

[0010] In a possible implementation, the impurity extraction deviation set is located in the impurity ratio parameter set according to the reuse association information set, and the following processing is performed:

[0011] Taking the multiple reuse-related indicators as comparison indicators, traverse the impurity ratio parameter set and hit M associated impurity ratio parameters, wherein the M associated impurity ratio parameters are mapped to M reuse-related indicators among the multiple reuse-related indicators; based on the M reuse-related indicators, M reuse-related requirements are mapped and called; using the M reuse-related requirements, traverse the M associated impurity ratio parameters to locate the impurity extraction deviation set, wherein the impurity extraction deviation set includes N impurity extraction deviations, and N is a positive integer less than or equal to M.

[0012] In a possible implementation, an analysis of the impurity removal associated steps is performed based on the impurity extraction deviation set, and process parameter configuration of the safe recycling system is performed based on the analysis result, and the following processing is performed:

[0013] Based on the impurity extraction deviation set, an analysis of impurity removal associated steps is performed to obtain K key processing processes; the impurity extraction deviation set is reorganized according to the K key processing processes to obtain K groups of impurity extraction deviations; based on the K groups of impurity extraction deviations, initial process parameters of the K key processing processes are optimized to obtain K updated process parameters; and the K updated process parameters are used to configure the process parameters of the safe reuse system.

[0014] In a possible implementation, the impurity removal associated step analysis is performed based on the impurity extraction deviation set to obtain K key processing processes, before which the following processing is performed:

[0015] Interact with the safe reuse system to obtain historical processing logs; perform data cleansing on the historical processing logs based on impurity processing types to obtain multiple impurity processing type sets for multiple process steps in the safe reuse system; store the multiple process steps and multiple impurity processing type sets based on knowledge graph mapping to generate an impurity removal related information library.

[0016] In a possible implementation, an impurity removal correlation step analysis is performed based on the impurity extraction deviation set to obtain K key processing processes, and the following processing is performed:

[0017] A first impurity extraction deviation is used to traverse the impurity removal associated information library to locate a first set of alternative steps, wherein the first impurity extraction deviation is any one of the impurity extraction deviation set; by analogy, N impurity extraction deviations in the impurity extraction deviation set are used to traverse the impurity removal associated information library to locate N sets of alternative steps; the N sets of alternative steps are combined and enumerated to obtain a plurality of combinations of alternative steps; repeated steps are eliminated for the plurality of combinations of alternative steps to obtain a plurality of updated step combinations; the number of steps is collected for the plurality of updated step combinations, and extreme value calls are performed based on the collected results to obtain a target step combination, wherein the target step combination includes the K key processing techniques.

[0018] In a possible implementation, initial process parameters of the K key processing processes are optimized based on the K groups of impurity extraction deviations to obtain K updated process parameters, and the following processing is performed:

[0019] A process parameter analysis library is pre-built, wherein the process parameter analysis library stores multiple process parameter analysis models of the multiple process steps; based on the K key processing processes, K process parameter analysis models are obtained by calling from the process parameter analysis library; the K groups of impurity extraction deviation mappings are synchronized to the K process parameter analysis models to obtain K groups of impurity removal process parameters; and the K groups of impurity removal process parameters are superimposed to obtain the K updated process parameters.

[0020] In a possible implementation, a process parameter analysis library is pre-built to perform the following processing:

[0021] A first impurity treatment type set for a first process step is extracted from the impurity removal associated information library, wherein the first process step is any one of the multiple process steps, and the first impurity treatment type set includes H impurity treatment types; data is called in the historical processing log with the first process step and the first impurity treatment type set as guidance to obtain H sample impurity extraction deviation sets and H sample impurity removal parameter sets; the H sample impurity extraction deviation sets and the H sample impurity removal parameter sets are used as training data to train and generate H process parameter analysis branches; after using the H impurity treatment types to identify the H process parameter analysis branches, the H process parameter analysis branches are connected in parallel to obtain a first process parameter analysis model; and so on, multiple process parameter analysis models for the multiple process steps are constructed, and the multiple process parameter analysis models are stored through the process parameter analysis library.

[0022] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0023] The method provided in the embodiment of the present application obtains an impurity analysis object by collecting samples of the dehydrated liquid to be treated; performs detection and analysis on the impurity analysis object to obtain an impurity ratio parameter set; presets a reuse association information set, and locates an impurity extraction deviation set in the impurity ratio parameter set according to the reuse association information set; performs an impurity removal association step analysis based on the impurity extraction deviation set, and configures the process parameters of the safe reuse system based on the analysis results; and uses the configured safe reuse system to remove impurities and reuse the dehydrated liquid to be treated. The method achieves the intelligentization and optimization of the dehydrated liquid treatment process, improves the treatment efficiency and water quality, and ensures the technical effect of safe reuse of the dehydrated liquid. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A schematic diagram of the process flow of the dewatering liquid treatment optimization method for the safe reuse system provided in this application;

[0025] Figure 2 A schematic diagram of a process for locating impurity extraction deviation sets in a dehydrated liquid processing optimization method for a safe reuse system provided in this application. DETAILED DESCRIPTION

[0026] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0027] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0028] In the following description, the term "first\second" involved is only to distinguish similar objects and does not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions. For example, a process, method, device, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are only for the purpose of describing the embodiments of the present application.

[0029] The present application provides a dehydration liquid treatment optimization method for a safe reuse system, which is used to solve the technical problem that the process step parameter setting of the dehydration liquid treatment process in the prior art is overly dependent on the operator's experience and intuition, resulting in unnecessary steps or omission of key steps in the dehydration liquid treatment process, thereby affecting the dehydration liquid treatment efficiency and the water quality stability of the obtained reused water. The dehydration liquid treatment process is intelligentized and optimized, the treatment efficiency and water quality are improved, and the safe reuse of the dehydration liquid is guaranteed.

[0030] Below, the technical solutions in the present invention will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments of the present invention. It should be understood that the present invention is not limited to the example embodiments described herein. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. It should also be noted that, for the convenience of description, only the parts related to the present invention are shown in the accompanying drawings, rather than all of them.

[0031] Examples, such as Figure 1 As shown, the present application provides a method for optimizing the treatment of dehydrated liquid for a safe reuse system, the method comprising:

[0032] A100: Collect samples from the dehydrated liquid to be processed to obtain impurity analysis objects.

[0033] A200: Detect and analyze the impurity analysis object to obtain an impurity ratio parameter set.

[0034] Specifically, it should be understood that the safe reuse system can effectively remove pollutants in the dehydrated liquid, reduce its impact on the environment, and make it meet the water quality requirements suitable for specific reuse purposes.

[0035] In this embodiment, a representative sample is first collected from the dehydrated liquid to be processed to obtain the impurity analysis object, which is collected for subsequent analysis to obtain detailed information about the impurities present in the dehydrated liquid.

[0036] The impurity analysis object is then processed by methods such as spectral analysis, mass spectrometry, titration testing, etc. to identify and quantify various inorganic and organic impurities present in the impurity analysis object, such as metal ions, organic matter, microorganisms, etc., to obtain the impurity ratio parameter set, wherein the impurity ratio parameter set includes the concentration data of each impurity in the dehydrated liquid to be treated.

[0037] A300: Preset a reuse association information set, and locate an impurity extraction deviation set in the impurity ratio parameter set according to the reuse association information set.

[0038] The reuse-related information set includes a plurality of reuse-related indicators and a plurality of reuse-related requirements.

[0039] In one embodiment, Figure 2 As shown, according to the reuse association information set in the impurity ratio parameter set, the impurity extraction deviation set is located, and the method step A300 provided in the present application also includes:

[0040] A310: Using the multiple reuse-related indicators as comparison indicators, traverse the impurity ratio parameter set and hit M associated impurity ratio parameters, wherein the M associated impurity ratio parameters are mapped to M reuse-related indicators among the multiple reuse-related indicators.

[0041] A320: Based on the M reuse-related indicators, the M reuse-related requirements are mapped and called.

[0042] A330: Using the M reuse-related requirements to traverse the M associated impurity ratio parameters, locate the impurity extraction deviation set, wherein the impurity extraction deviation set includes N impurity extraction deviations, where N is a positive integer less than or equal to M.

[0043] Specifically, in this embodiment, the reuse-related index is a key parameter for evaluating whether the dehydrated liquid is suitable for reuse, including pH value, dissolved oxygen, chemical oxygen demand (COD), heavy metal content, etc. For each reuse-related index, a maximum concentration value is defined as a reuse-related requirement. The corresponding impurity concentration in the dehydrated liquid must be lower than this value to meet the safety standard for reuse. Based on this, this embodiment establishes a reuse-related information set including multiple reuse-related indexes and their corresponding maximum concentration values ​​(reuse-related requirements).

[0044] Taking the multiple reuse associated indicators as comparison indicators, the impurity ratio parameter set is traversed to identify which parameters in the impurity ratio parameter set are related to the reuse associated indicators, thereby hitting M associated impurity ratio parameters corresponding to the M reuse associated indicators.

[0045] Based on the M reuse-related indicators, corresponding maximum allowable concentration values ​​are searched in the multiple reuse-related requirements to obtain M reuse-related requirements.

[0046] The M associated impurity ratio parameters are traversed using the M reuse associated requirements to determine that the associated impurity ratio parameters exceed the corresponding reuse associated requirements, and the N specific impurities that need to be optimized correspond to N impurity extraction deviations as the impurity extraction deviation set, where N is a positive integer less than or equal to M.

[0047] This embodiment achieves accurate identification of the impurity parameters that need to be treated, determines the target concentrations that need to be reached, and calculates the adjustment range required to achieve the target concentration, providing a clear direction and goal for subsequent process optimization and treatment, ensuring that the dehydrated liquid can be effectively treated and safely reused.

[0048] A400: Perform impurity removal associated step analysis based on the impurity extraction deviation set, and configure process parameters of the safe reuse system based on the analysis results.

[0049] In one embodiment, an impurity removal associated step analysis is performed based on the impurity extraction deviation set, and a process parameter configuration of a safe recycling system is performed based on the analysis result. The method step A400 provided in the present application further includes:

[0050] A410: Perform impurity removal related step analysis based on the impurity extraction deviation set to obtain K key processing processes.

[0051] A420: Reorganize the impurity extraction deviation set according to the K key processing processes to obtain K groups of impurity extraction deviations.

[0052] A430: Optimize initial process parameters of the K key processing processes based on the K groups of impurity extraction deviations to obtain K updated process parameters.

[0053] A440: Use the K updated process parameters to configure the process parameters of the safe reuse system.

[0054] In one embodiment, the impurity removal associated step analysis is performed based on the impurity extraction deviation set to obtain K key processing processes. Previously, the method step A410 provided in the present application also includes:

[0055] A411: Interact with the security reuse system to obtain historical processing logs.

[0056] A412: Clean the data of the historical processing log based on the impurity processing type to obtain multiple impurity processing type sets for multiple process steps in the safe reuse system.

[0057] A413: Store the multiple process steps and multiple impurity treatment type sets based on the knowledge graph mapping to generate an impurity removal related information library.

[0058] In one embodiment, based on the impurity extraction deviation set, impurity removal associated step analysis is performed to obtain K key processing processes. The method step A411 provided in the present application also includes:

[0059] A414: Use a first impurity extraction deviation to traverse the impurity removal associated information library to locate a first set of backup steps, wherein the first impurity extraction deviation is any one of the impurity extraction deviation set.

[0060] A415: Similarly, N impurity extraction deviations in the impurity extraction deviation set are used to traverse the impurity removal association information library to locate N spare step sets.

[0061] A416: Perform combination enumeration on the N sets of alternative steps to obtain multiple combinations of alternative steps.

[0062] A417: Eliminate duplicate steps from the multiple backup step combinations to obtain multiple updated step combinations.

[0063] A418: Collect the number of steps for the multiple update step combinations, and perform extreme value calls based on the collected results to obtain a target step combination, wherein the target step combination includes the K key processing processes.

[0064] In one embodiment, the initial process parameters of the K key processing processes are optimized based on the K groups of impurity extraction deviations to obtain K updated process parameters. The method step A430 provided in the present application further includes:

[0065] A431: Pre-constructing a process parameter analysis library, wherein the process parameter analysis library stores a plurality of process parameter analysis models of the plurality of process steps.

[0066] A432: Based on the K key processing processes, obtain K process parameter analysis models from the process parameter analysis library.

[0067] A433: Synchronize the K groups of impurity extraction deviation mappings to the K process parameter analysis models to obtain K groups of impurity removal process parameters.

[0068] A434: Superimpose the K groups of impurity removal process parameters to obtain the K updated process parameters.

[0069] In one embodiment, a process parameter analysis library is pre-built, and step A431 of the method provided in the present application further includes:

[0070] A4311: Extract a first impurity treatment type set for a first process step from the impurity removal associated information library, wherein the first process step is any one of the multiple process steps, and the first impurity treatment type set includes H impurity treatment types.

[0071] A4311: Using the first process step and the first impurity processing type set as a guide, data is called in the historical processing log to obtain H sample impurity extraction deviation sets and H sample impurity removal parameter sets.

[0072] A4312: Using the H sample impurity extraction deviation sets and the H sample impurity removal parameter sets as training data, training generates H process parameter analysis branches.

[0073] A4313: After using the H impurity treatment types to identify the H process parameter analysis branches, the H process parameter analysis branches are connected in parallel to obtain a first process parameter analysis model.

[0074] A4314: Similarly, multiple process parameter analysis models of the multiple process steps are constructed, and the multiple process parameter analysis models are stored in the process parameter analysis library.

[0075] Specifically, in this embodiment, data interaction is performed with the safe reuse system, processing records generated by the safe reuse system during past operation are collected, and historical processing logs are obtained. The historical processing logs specifically include multiple impurity removal logs of multiple process steps in the safe reuse system, and each impurity removal log specifically records the historical impurity removal type of the corresponding process step and the process parameter settings under different impurity concentrations.

[0076] Data cleaning of the historical processing log is performed based on the impurity processing type to obtain multiple impurity processing type sets for multiple process steps in the safe reuse system, wherein the impurity processing type sets reflect all impurity types that can be processed by the corresponding process steps.

[0077] The multiple process steps and multiple impurity treatment type sets are stored based on the knowledge graph mapping, and an impurity removal associated information library is generated. The impurity removal associated information library is used to store and retrieve information about specific impurities that can be treated by different process steps.

[0078] The first impurity extraction deviation is used to traverse the impurity removal associated information library, and the relevant process steps that can process this impurity are searched in the impurity removal associated information library to obtain a first set of alternative steps. Similarly, step A414 is repeated for each impurity in the impurity extraction deviation set, and the impurity removal associated information library is traversed to locate the alternative step set corresponding to each impurity to obtain N sets of alternative steps.

[0079] The N spare step sets are combined and enumerated to generate all step combinations that can effectively correct the impurity concentration of the impurity extraction deviation set, and obtain multiple spare step combinations.

[0080] The multiple alternative step combinations obtained in step A416 are checked, repeated or redundant steps are eliminated, and multiple updated step combinations are obtained. It should be understood that in the updated step combinations, there is a situation where one process step undertakes two or more impurity concentration adjustment tasks.

[0081] The number of steps is collected for the multiple update step combinations, the number of steps included in each combination is counted, and extreme value calls are made based on the collected results to select the combination with the least number of steps to obtain a target step combination, wherein the target step combination includes the K key processing processes.

[0082] This embodiment learns from historical data and optimizes the processing flow, selects the most appropriate combination of process steps to treat specific impurities, and achieves the technical effect of improving the processing of dehydrated liquid and ensuring the safe reuse of dehydrated liquid.

[0083] The impurity extraction deviation set is reorganized according to the K key processing processes to obtain K groups of impurity extraction deviations, and each group of impurity extraction deviations is a specific impurity concentration adjustment task of each key processing process.

[0084] A process parameter analysis library is pre-constructed, wherein the process parameter analysis library stores multiple process parameter analysis models of the multiple process steps, each process parameter analysis model can automatically analyze the parameter setting of the process step according to the input impurity concentration, and the construction process of the process parameter analysis library is as follows:

[0085] All types of impurities whose concentrations can be optimized in the first process step are extracted from the impurity removal association information library to obtain a first impurity treatment type set, wherein the first process step is any one of the multiple process steps, and the first impurity treatment type set includes H impurity treatment types.

[0086] Data is called up in the historical processing log under the guidance of the first process step and the first impurity treatment type set, including H sample impurity extraction deviation sets and H sample impurity removal parameter sets when the first process step adjusts the concentration of impurities of the H impurity treatment types, wherein a mapping relationship exists between the H sample impurity extraction deviation sets and the H sample impurity removal parameter sets.

[0087] A standard process parameter analysis branch is pre-constructed, and the standard process parameter analysis branch is constructed based on the model structure of the back-propagation neural network. The comparison input is the impurity concentration, and the output is the process parameter setting (sample impurity removal parameter) required when the concentration is reduced to the corresponding reuse-related requirement.

[0088] A conventional training method of a back propagation neural network is adopted, the H sample impurity extraction deviation sets and H sample impurity removal parameter sets are used as training data, the model parameter adjustment of the standard process parameter analysis branch is performed multiple times, and H process parameter analysis branches are generated through training.

[0089] After the H process parameter analysis branches are identified by the H impurity treatment types, the H process parameter analysis branches are connected in parallel to obtain a first process parameter analysis model.

[0090] By analogy, a plurality of process parameter analysis models of the plurality of process steps are constructed, and the plurality of process parameter analysis models are stored in the process parameter analysis library.

[0091] The specific application of the process parameter analysis library is as follows:

[0092] A second process parameter analysis model is obtained by calling from the process parameter analysis library based on the process steps of a second key process, wherein the second key process is any one of the K key processes. A second group of impurity extraction deviations is extracted from the K groups of impurity extraction deviations based on the second key process, wherein the second group of impurity extraction deviations includes a plurality of impurity extraction deviations of a plurality of impurity processing types.

[0093] Based on the impurity processing type, multiple impurity extraction deviations are mapped and synchronized to multiple process parameter analysis branches of the second process parameter analysis model to obtain multiple impurity removal process parameters to form a second group of impurity removal process parameters.

[0094] By analogy, the same method is adopted to obtain K process parameter analysis models based on the K key processing processes from the process parameter analysis library, and the K groups of impurity extraction deviation mappings are synchronized to the K process parameter analysis models to obtain K groups of impurity removal process parameters. It should be understood that if a process step is responsible for removing multiple impurities, then a group of impurity removal process parameters corresponding to this step is a combination of all these impurity processing requirements.

[0095] The K groups of impurity removal process parameters are sequentially sorted and superimposed within the group to obtain the K updated process parameters, the K updated process parameters are used to pre-configure the process parameters of the safe reuse system, and the parameter settings of the K key processing processes are dynamically adjusted during the impurity removal process of the dehydrated liquid to be treated.

[0096] This embodiment realizes the intelligence and optimization of the dehydration liquid treatment process by combining historical data analysis, machine learning models and automated process parameter optimization, improves the treatment efficiency and water quality, and ensures the safe reuse of the dehydration liquid.

[0097] A500: The configured safe recycling system is used to remove impurities and reuse the dehydrated liquid to be treated.

[0098] Specifically, in this embodiment, the K updated process parameters are used to pre-configure the process parameters of the safe reuse system, and the parameter settings of the K key processing processes are dynamically adjusted during the impurity removal process of the dehydrated liquid to be treated.

[0099] This embodiment achieves the technical effect of intelligentization and optimization of the dehydration liquid treatment process, improves the treatment efficiency and water quality, and ensures the safe reuse of the dehydration liquid.

[0100] Any of the methods or steps described above may be stored as computer instructions or programs in various types of computer memories, and the computer instructions or programs may be recognized by various types of computer processors to implement any of the methods or steps described above.

[0101] The above specific implementation manner does not constitute a limitation to the protection scope of the present application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be performed in an order different from that in the embodiment and can still achieve the desired results. In addition, the process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A method for optimizing the treatment of dehydrated liquid for a safe reuse system, characterized in that: The method comprises: Collect samples of the dehydrated liquid to be treated to obtain impurity analysis objects; Performing detection and analysis on the impurity analysis object to obtain an impurity ratio parameter set; Presetting a reuse association information set, and locating an impurity extraction deviation set in the impurity ratio parameter set according to the reuse association information set; Performing an impurity removal associated step analysis based on the impurity extraction deviation set, and configuring process parameters of a safe recycling system based on the analysis results; The configured safe recycling system is used to remove impurities and reuse the dehydrated liquid to be treated.

2. The dewatering liquid treatment optimization method for a safe reuse system according to claim 1, characterized in that: The reuse-related information set includes a plurality of reuse-related indicators and a plurality of reuse-related requirements.

3. The dewatering liquid treatment optimization method for a safe reuse system according to claim 2, characterized in that: According to the reuse association information set in the impurity ratio parameter set, locating the impurity extraction deviation set, the method further includes: Taking the multiple reuse-related indicators as comparison indicators, traversing the impurity ratio parameter set, and hitting M associated impurity ratio parameters, wherein the M associated impurity ratio parameters are mapped to M reuse-related indicators among the multiple reuse-related indicators; Based on the M reuse-related indicators, calling the M reuse-related requirements in the plurality of reuse-related requirements mappings; The M associated impurity ratio parameters are traversed using the M reuse associated requirements to locate the impurity extraction deviation set, wherein the impurity extraction deviation set includes N impurity extraction deviations, where N is a positive integer less than or equal to M.

4. The dewatering liquid treatment optimization method for a safe reuse system according to claim 3, characterized in that: Based on the impurity extraction deviation set, an analysis of impurity removal associated steps is performed, and based on the analysis results, a process parameter configuration of a safe recycling system is performed, and the method further includes: Perform impurity removal correlation step analysis based on the impurity extraction deviation set to obtain K key processing processes; Reorganize the impurity extraction deviation set according to the K key processing processes to obtain K groups of impurity extraction deviations; Optimizing initial process parameters of the K key processing processes based on the K groups of impurity extraction deviations to obtain K updated process parameters; The K updated process parameters are used to configure the process parameters of the safe reuse system.

5. The dewatering liquid treatment optimization method for a safe reuse system according to claim 4, characterized in that: Before performing impurity removal correlation step analysis based on the impurity extraction deviation set to obtain K key processing processes, the method further includes: Interact with the security reuse system to obtain historical processing logs; Clean the data of the historical processing log based on the impurity processing type to obtain multiple impurity processing type sets for multiple process steps in the safe reuse system; The multiple process steps and multiple impurity treatment type sets are stored based on the knowledge graph mapping to generate an impurity removal related information library.

6. The dewatering liquid treatment optimization method for a safe reuse system according to claim 5, characterized in that: Based on the impurity extraction deviation set, impurity removal correlation step analysis is performed to obtain K key processing processes, and the method further includes: Using a first impurity extraction deviation to traverse the impurity removal association information library to locate a first set of backup steps, wherein the first impurity extraction deviation is any one of the impurity extraction deviation set; By analogy, N impurity extraction deviations in the impurity extraction deviation set are used to traverse the impurity removal association information library to locate N spare step sets; Combining and enumerating the N sets of alternative steps to obtain multiple combinations of alternative steps; Eliminating repeated steps from the plurality of standby step combinations to obtain a plurality of updated step combinations; The number of steps is collected for the multiple update step combinations, and extreme value calls are made based on the collected results to obtain a target step combination, wherein the target step combination includes the K key processing processes.

7. The dewatering liquid treatment optimization method for a safe reuse system according to claim 5, characterized in that: Optimizing initial process parameters of the K key processing processes based on the K groups of impurity extraction deviations to obtain K updated process parameters, the method further comprising: Pre-building a process parameter analysis library, wherein the process parameter analysis library stores a plurality of process parameter analysis models of the plurality of process steps; Based on the K key processing processes, K process parameter analysis models are obtained by calling from the process parameter analysis library; Synchronize the K groups of impurity extraction deviation mappings to the K process parameter analysis models to obtain K groups of impurity removal process parameters; The K groups of impurity removal process parameters are superimposed to obtain the K updated process parameters.

8. The dewatering liquid treatment optimization method for a safe reuse system according to claim 7, characterized in that: Pre-building a process parameter analysis library, the method further comprising: Extracting a first impurity treatment type set for a first process step from the impurity removal associated information library, wherein the first process step is any one of the multiple process steps, and the first impurity treatment type set includes H impurity treatment types; Using the first process step and the first impurity processing type set as a guide, data is called in the historical processing log to obtain H sample impurity extraction deviation sets and H sample impurity removal parameter sets; The H sample impurity extraction deviation sets and the H sample impurity removal parameter sets are used as training data to generate H process parameter analysis branches through training; After identifying the H process parameter analysis branches by using the H impurity treatment types, the H process parameter analysis branches are connected in parallel to obtain a first process parameter analysis model; By analogy, a plurality of process parameter analysis models of the plurality of process steps are constructed, and the plurality of process parameter analysis models are stored in the process parameter analysis library.

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